Conformal Region Classification with Instance-Transfer Boosting

摘要

Conformal region classification focuses on developing region classifiers; i.e., classifiers that output regions (sets) of classes for new test instances. 2,13,16 Conformal region classifiers have been proven to be valid for any significance level epsilon is an element of [0, 1] in the sense that the probability the class regions do not contain the true instances' classes does not exceed e. In practice, however, conformal region classifiers need to be also efficient; i.e., they have to output non-empty and relatively small class regions.